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MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity

Overview of attention for article published in BMC Bioinformatics, January 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
2 blogs

Citations

dimensions_citation
663 Dimensions

Readers on

mendeley
255 Mendeley
citeulike
3 CiteULike
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Title
MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-1
Pubmed ID
Authors

Wen Huang, Naoki Takebayashi, Yan Qi, Michael J Hickerson

Abstract

MTML-msBayes uses hierarchical approximate Bayesian computation (HABC) under a coalescent model to infer temporal patterns of divergence and gene flow across codistributed taxon-pairs. Under a model of multiple codistributed taxa that diverge into taxon-pairs with subsequent gene flow or isolation, one can estimate hyper-parameters that quantify the mean and variability in divergence times or test models of migration and isolation. The software uses multi-locus DNA sequence data collected from multiple taxon-pairs and allows variation across taxa in demographic parameters as well as heterogeneity in DNA mutation rates across loci. The method also allows a flexible sampling scheme: different numbers of loci of varying length can be sampled from different taxon-pairs.

Mendeley readers

The data shown below were compiled from readership statistics for 255 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 4%
Brazil 4 2%
France 3 1%
United Kingdom 3 1%
Mexico 3 1%
Germany 1 <1%
Sweden 1 <1%
Czechia 1 <1%
Netherlands 1 <1%
Other 4 2%
Unknown 224 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 24%
Student > Ph. D. Student 59 23%
Student > Master 32 13%
Professor > Associate Professor 20 8%
Student > Bachelor 19 7%
Other 49 19%
Unknown 16 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 189 74%
Biochemistry, Genetics and Molecular Biology 19 7%
Environmental Science 7 3%
Linguistics 2 <1%
Nursing and Health Professions 2 <1%
Other 9 4%
Unknown 27 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 March 2014.
All research outputs
#196,519
of 3,627,694 outputs
Outputs from BMC Bioinformatics
#135
of 2,289 outputs
Outputs of similar age
#7,795
of 97,690 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 102 outputs
Altmetric has tracked 3,627,694 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,289 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 97,690 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.